Principal Software Engineer - Semantic Views

Principal Engineer · Principal · Full Time

US-CA-Menlo ParkUSD 264k – 380k1d ago
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Role

What you'll do.

Principal Software Engineer on Snowflake's Semantic Views team, responsible for designing and maintaining the semantic layer that powers enterprise data analytics and AI-driven agent queries. This senior engineering role requires 15+ years of systems and data software expertise, deep knowledge of query compilation and optimization, and the ability to architect solutions that ensure correctness and performance at petabyte scale while mentoring technical talent.

Responsibilities

  • Architect Semantic Layer Infrastructure: Design and develop the semantic modeling layer that translates semantic queries into optimized, high-performance SQL, serving as the foundational system for Snowflake's governed, reusable business definitions across BI tools, SQL interfaces, and AI agents.
  • Query Compilation and Optimization: Own compiler elements and query rewriter systems that expand semantic queries into correct SQL over petabyte-scale data, ensuring optimal performance and scalability across interactive analytics workloads.
  • Strategic Product Roadmap Influence: Create architecture specifications, guide product direction, and take ownership of new semantic layer capabilities including metrics, dimensions, relationships, and governance frameworks that align with customer needs and platform strategy.
  • Correctness and Performance Assurance: Establish and maintain rigorous standards ensuring semantic queries produce consistently correct results while meeting demanding performance and scale requirements, preventing data inconsistencies and analytical errors.
  • AI and Analytics Integration: Partner with Cortex and AI teams to position the semantic layer as the reliable foundation for natural-language queries and agent-driven analytics, enabling trustworthy data insights across emerging AI use cases.
  • Technical Leadership and Mentorship: Mentor and develop engineering talent on the team, raise the technical bar through code reviews and architectural guidance, and foster a culture of excellence in systems design and problem-solving.
  • Operational Readiness and Support: Ensure operational excellence for shipped features, maintain customer commitments on correctness, availability, and performance, and establish monitoring and incident response protocols for semantic layer systems.
  • Complex Problem-Solving: Apply strong analytical and software engineering skills to solve real business needs at large scale, identifying creative solutions to ambiguous technical challenges that span query language semantics, metadata management, and AI-driven analytics.

Qualifications

What we look for.

Technical

  • Query Compilation and Optimization

    Deep expertise in query compilation techniques, cost-based optimization, query rewriting, and the ability to design systems that transform semantic queries into high-performance SQL at scale.

  • Database and Query Engine Internals

    Thorough understanding of database architecture, query execution engines, and internal data management systems, or demonstrated experience building semantic/metrics layers and BI infrastructure.

  • SQL Semantics and Relational Modeling

    Strong grasp of SQL semantics, relational data modeling principles, and deep appreciation for result correctness as a non-negotiable requirement in analytical systems.

  • Large-Scale Data Systems

    Proven ability to design, build, and support data infrastructure handling petabyte-scale workloads, with understanding of trade-offs between expressiveness, correctness, performance, and operational cost.

  • Computer Science Fundamentals

    Strong foundations in data structures, algorithms, computational complexity analysis, and principled software architecture that enable sound technical decision-making.

Education

  • Bachelor's Degree in Computer Science

    BS in Computer Science required; advanced degree (Master's or PhD) is preferred and valued for advanced theoretical and research foundations.

Experience

  • 15+ Years Large-Scale Systems Engineering

    Minimum 15 years designing, building, and supporting large-scale data or systems software in production environments at scale.

  • Query Engine or Semantic Layer Development

    Substantial hands-on experience with at least one of: query compilation and optimization, database query engine internals, semantic/metrics layer architecture, or BI and analytics infrastructure platforms.

  • Cross-Functional Collaboration

    Demonstrated ability to work effectively across engineering teams in multiple geographic locations, balancing technical excellence with business priorities and customer needs.

  • Technical Leadership and Mentorship

    Track record of mentoring engineers, raising technical standards, and influencing architectural decisions across teams.

Skills

Required

  • Query Language Design and Semantics

    Expertise in designing query languages, understanding semantic correctness, and implementing systems that preserve query semantics across transformations.

  • SQL and Relational Database Systems

    Deep fluency with SQL, relational data models, and understanding of how relational semantics must be preserved in query rewriting and optimization.

  • Systems Architecture and Design

    Advanced ability to architect large-scale systems with clear abstractions, well-defined interfaces, and scalable designs that handle petabyte-scale workloads.

  • Performance Engineering and Optimization

    Expertise in performance analysis, optimization techniques, and making informed trade-offs between performance, correctness, and system complexity.

  • Problem-Solving and Ambiguity Navigation

    Strong track record of identifying and implementing creative solutions to complex, ambiguous problems with multiple competing requirements.

  • Object-Oriented Programming

    Proficiency in Java or similar object-oriented languages, with strong software engineering practices and design patterns.

Preferred

  • AI and Machine Learning Infrastructure

    Nice to have

    Experience working with AI and machine learning systems, understanding how AI agents interact with data platforms, or building systems to support emerging AI use cases.

  • BI and Analytics Tools Integration

    Nice to have

    Familiarity with Business Intelligence tools, analytics platforms, and understanding how semantic layers connect to BI ecosystems.

  • Compiler and Language Implementation

    Nice to have

    Background in compiler design, language implementation, abstract syntax trees, or formal language semantics provides valuable perspective for query compilation work.

  • Cloud Data Warehouse Experience

    Nice to have

    Prior experience with cloud data warehousing platforms, distributed query processing, or petabyte-scale analytics systems.

  • Open Source Contributions

    Nice to have

    Contributions to significant open-source database, analytics, or compiler projects demonstrate deep technical expertise and collaborative problem-solving.

Tech stack

Languages

JavaSQLPython

Frameworks

Snowflake CortexApache Calcite

Databases

Snowflake Cloud Data PlatformRelational Database Systems

Tools

Query Optimization and Analysis ToolsVersion Control and Collaborative DevelopmentMonitoring and Observability Platforms

Other

Semantic Modeling and Metadata FrameworksQuery Compilation and AST ManipulationDistributed Systems Architecture

Compensation

Pay and benefits.

Base·USD 264,000 – 379,500

Equity·Stock options

Benefits

  • Competitive Equity Compensation

    Participate in Snowflake's equity program, aligning personal financial success with company growth and long-term value creation in the cloud data platform market.

  • Comprehensive Health and Wellness Coverage

    Robust medical, dental, and vision insurance plans, plus mental health support and wellness programs designed for high-performing technical professionals.

  • Flexible Work Arrangements

    Work flexibility supporting both focused technical work and collaborative team engagement, with options for remote work as negotiated with your team.

  • Professional Development and Learning

    Access to technical education, conference attendance budgets, training opportunities, and mentorship programs to advance your expertise and career growth.

  • Retirement Planning

    Competitive 401(k) matching and retirement savings programs helping you build long-term financial security.

  • Time Off and Work-Life Balance

    Generous paid time off, parental leave, and sabbatical opportunities ensuring sustainable work practices for leadership-level engineers.

  • Innovation and Impact Opportunities

    Direct influence over strategic product direction, the chance to work on foundational systems impacting thousands of enterprises, and autonomy to drive technical excellence.

Process

Interview steps.

  1. 01

    Initial Screening and Background Discussion

    Recruiter or hiring manager conducts initial conversation to understand your background, motivation for the role, and alignment with Snowflake's AI-native culture and fast-moving environment.

  2. 02

    Technical Architecture and Systems Design Interview

    Deep-dive discussion with engineering leadership on your experience designing large-scale systems, query optimization approaches, semantic layer architecture, and how you approach complex technical trade-offs.

  3. 03

    Query Compilation and Optimization Technical Deep-Dive

    Technical interview focused on query compilation, semantic correctness, query rewriting strategies, and optimization techniques, potentially including whiteboarding or code discussion of complex scenarios.

  4. 04

    Database Systems and Correctness Expertise

    Conversation exploring your depth of understanding in database internals, SQL semantics, handling edge cases in query transformation, and your philosophy on ensuring analytical correctness.

  5. 05

    Leadership, Mentorship, and Collaboration

    Discussion of your experience mentoring engineers, raising technical standards, working across distributed teams, and driving architectural decisions in matrix organizations.

  6. 06

    Problem-Solving and Ambiguity Navigation

    Open-ended technical discussion or case study exploring how you approach undefined problems, identify the right solution, and balance competing requirements in systems design.

  7. 07

    Executive Alignment and Vision Discussion

    Conversation with senior engineering leadership or director about strategic vision for semantic layers, AI-driven analytics, and your perspective on future directions in data platforms.

  8. 08

    Offer Discussion and Negotiation

    Discussion of compensation, equity, and role details, with clear communication about expectations, team structure, and growth opportunities within Snowflake's engineering organization.

Full posting

Original listing.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

We are the Snowflake Semantic Views team. We build the semantic layer at the core of the Snowflake platform — the system that lets customers define logical data models (tables, dimensions, metrics, and the relationships between them) once, and then query them consistently across BI tools, SQL, and AI agents. Semantic Views turn raw physical schemas into governed, reusable business definitions, so that "revenue," "active customer," or "gross margin" mean the same thing no matter who or what is asking. We own the semantic model itself, compiler elements and query rewriter that expand semantic queries into optimized SQL over petabyte-scale data, and the surfaces that expose this layer to Cortex Analyst and the broader agent ecosystem. Our work sits at the intersection of query language, metadata, and AI-driven analytics, and it is foundational to how Snowflake customers get trustworthy answers from their data.

As a Principal Software Engineer at Snowflake you will:

  • Solve real business needs at large scale by applying your software engineering and analytical problem-solving skills.

  • Design, develop, and support the semantic modeling layer that translates semantic queries into correct, high-performance SQL.

  • Create architecture and design, influence the semantic layer roadmap, and take ownership over new capabilities spanning metrics, dimensions, relationships, and governance.

  • Ensure semantic queries produce correct results while meeting the performance and scale demands of interactive analytics over petabyte-scale data.

  • Partner with the Cortex and AI teams to make the semantic layer the reliable grounding source for natural-language and agent-driven analytics.

  • Understand the trade-offs between expressiveness, correctness, performance, and cost, and build solutions that hold up as usage grows.

  • Mentor and grow engineers, and raise the technical bar across the team.

  • Ensure operational readiness of the features we ship and meet our commitments to customers on correctness, availability, and performance.

Our ideal Principal Software Engineer will have:

  • 15+ years of industry experience designing, building, and supporting large-scale data or systems software.

  • Strong computer science fundamentals including data structures, algorithms, and complexity analysis.

  • Deep experience with at least one of: query compilation and optimization, database or query engine internals, semantic/metrics layers, or BI and analytics infrastructure.

  • A strong grasp of SQL semantics and relational modeling, and an appreciation for why correctness of results is non-negotiable.

  • Fluency in Java or another similar object-oriented language is preferred.

  • A track record of identifying and implementing creative solutions to complex, ambiguous problems.

  • Ability to work effectively across engineering teams in multiple locations.

  • BS in Computer Science; Masters or PhD preferred.

Why join the engineering team at Snowflake?

  • Build an industry-leading Cloud Data and AI Platform.

  • Work on one of the most strategically important layers for both traditional BI and the emerging world of AI agents that query enterprise data.

  • Solve challenging technical problems in query compilation, semantics, performance at scale, and correctness.

  • Work closely with our customers and partners, understand their use cases and needs, and think strategically about the right problem to solve at the right time.

  • Join a world-class team of both industry veterans and rising stars.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

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